An Efficient Streaming Algorithm for Approximating Graphlet Distributions
Summary: A streaming k-graphlet sampler trades O(1/c) passes for Õ(n^(1+c)) memory, improving Bourreau et al.’s O(log n)-pass algorithm. It is near-optimal under their lower bound and yields orders-of-magnitude gains on mildly dense graphs. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Marco Bressan (University of Milan)
- 2. T-H. Hubert Chan (University of Hong Kong)
- 3. Qipeng Kuang (University of Hong Kong)
- 4. Mauro Sozio (Libera Universita Internazionale degli Studi Sociali Guido Carli)
BibTeX Citation
@inproceedings{bressan_sigmod26,
title = {{An Efficient Streaming Algorithm for Approximating Graphlet Distributions}},
author = {Bressan, Marco and Chan, T-H. Hubert and Kuang, Qipeng and Sozio, Mauro},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802010},
url = {https://dl.acm.org/doi/10.1145/3802010},
year = {2026}
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Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 564 | Densest Subgraph in Streaming and MapReduce | 2012 | VLDB | 0.00016485347 |
| 793 | Streaming Algorithms for k-core Decomposition | 2013 | VLDB | 0.00013978774 |
| 1,103 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB | 0.000121583 |
| 1,958 | A General Framework for Estimating Graphlet Statistics via Random Walk | 2017 | VLDB | 9.4093057e-05 |
| 3,028 | Motivo: fast motif counting via succinct color coding and adaptive sampling | 2019 | VLDB | 7.8349117e-05 |
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